code: def attention_output_dim(self):
      context_dim = (
          self.config["num-left-inputs"]
          + self.config["num-right-inputs"]
          + 1
      )
      num_heads = self.config["num-heads"]
      value_dim = self.config["value-dim"]
      return num_heads * (
          value_dim
          + (context_dim if self.config["output-context"] else 0)
      )
  
file_path: espnet/egs2/librispeech_100/asr1/steps/libs/nnet3/xconfig/attention.py
imports: from __future__ import print_function
  from __future__ import division
  import math
  import re
  import sys
  from libs.nnet3.xconfig.basic_layers import XconfigLayerBase
label_desc: Use image node_id 6 for calling the XconfigAttentionLayer obj's underlying member method code with example usage: obj.attention_output_dim() and returns: unknown